The article introduces a method to test the accuracy of density forecasts by comparing them to a series of random variables. This method uses copula-based stationary Markov processes to assess if the forecasts are correct or if there are alternative patterns in the data. The tests can detect various types of patterns, such as skewed distributions and different types of dependencies. Additionally, the method can identify if the forecasting model is correctly specified.